title: Design and implementation of a low power mobile CPU based embedded system for artificial leg control.
abstract: This paper presents the design and implementation of a new neural-machine-interface (NMI) for control of artificial legs. The requirements of high accuracy, real-time processing, low power consumption, and mobility of the NMI place great challenges on the computation engine of the system. By utilizing the architectural features of a mobile embedded CPU, we are able to implement our decision-making algorithm, based on neuromuscular phase-dependant support vector machines (SVM), with exceptional accuracy and processing speed. To demonstrate the superiority of our NMI, real-time experiments were performed on an able bodied subject with a 20 ms window increment. The 20 ms testing yielded accuracies of 99.94% while executing our algorithm efficiently with less than 11% processor loads.
authors.forename: Robert
authors.initials: R
authors.lastname: Hernandez
authors.forename: Qing
authors.initials: Q
authors.lastname: Yang
authors.forename: He
authors.initials: H
authors.lastname: Huang
authors.forename: Fan
authors.initials: F
authors.lastname: Zhang
authors.forename: Xiaorong
authors.initials: X
authors.lastname: Zhang
mesh_terms: D000465:Algorithms; D001186:Artificial Limbs; D062207:Brain-Computer Interfaces; D016002:Discriminant Analysis; D004576:Electromyography; D006801:Humans; D007866:Leg; D010363:Pattern Recognition, Automated; D012984:Software; D060388:Support Vector Machine